Conventionally, a method has been known, in which a three-dimensional original image (three-dimensional volume data) is generated from a tomographic image group scanned by an X-ray CT (Computed Tomography) apparatus, an MRI (Magnetic Resonance Imaging) apparatus, etc. to generate an image appropriate for diagnosis (hereinafter, referred to as “diagnostic image”) to display it after a specific tissue is extracted or eliminated from the three-dimensional original image. As the diagnostic image, for example, a three-dimensional volume rendering image, an MIP (Maximum Intensity Projection) image, etc. are created. Specifically, in case of observing blood vessel running in the head, a boning MIP image in which bone regions including a skull, cartilage, etc. were eliminated from the above tomographic image group may be generated.
By the way, in order to generate a diagnostic image in which a specific tissue was extracted or eliminated as described above, a method to automatically extract a certain organ region from an original image using a computer etc. is proposed. As the extraction method, for example, there is a region growing method etc. In the region growing method, a computer determines whether predetermined threshold conditions are satisfied for a pixel of a starting point or surrounding pixels including the pixel when an operator specifies the pixel of the starting point in an image and extends the pixels as an extraction region in a case where the conditions are satisfied.
In the patent literature 1, a method to prevent overextraction due to a few connected pixels when region extraction by the region growing method is performed is disclosed. This method extends a region only when pixels at a predetermined ratio satisfy conditions in sense regions which range to the extraction region and are comprised of multiple pixels. Also, in the patent literature 2, a method to distinguish tissues difficult to separate such as the cancellous bone, bone marrow, etc. which are internal tissues of a bone is disclosed. Specifically, it is described that a pixel value histogram of an MR image including the cancellous bone and bone marrow is created to calculate a cancellous bone volume fraction more precisely to separate the both by fitting with three normal distribution curves (values of the cancellous bone, the bone marrow, and the middle of the both).